Decoding Spontaneous Emotional States in the Human Brain.

Journal Article

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Full Text

Duke Authors

Cited Authors

  • Kragel, PA; Knodt, AR; Hariri, AR; LaBar, KS

Published Date

  • September 14, 2016

Published In

Volume / Issue

  • 14 / 9

Start / End Page

  • e2000106 -

PubMed ID

  • 27627738

Electronic International Standard Serial Number (EISSN)

  • 1545-7885

International Standard Serial Number (ISSN)

  • 1544-9173

Digital Object Identifier (DOI)

  • 10.1371/journal.pbio.2000106

Language

  • eng